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Mathematics, Education
University -
Professional Development
Machine Learning (Quiz-3)
37 questions
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- 1. Multiple Choice
What is Classification?
The process of predicting the class of given data points.
It predicts infinite set values.
It is unsupervised technique.
It is part of Reinforcement Learning.
- 2. Multiple Choice
Which problems comes under Classification?
Review Analyser
Weather Prediction
Mood Detectors
University Prediction
- 3. Multiple Choice
Which curve is perfect example of Classification?
- 4. Multiple Choice
Which model is the best choice for fraud detection?
Precision = 0.8, Recall = 0.4
Precision = 0.4, Recall = 0.8
Precision = 0.7, Recall = 0.7
- 5. Multiple Choice
What is the correct for the red dot for the application of diabetes prediction?
Setting threshold = 0, All samples have diabetes
Setting threshold = 1, All samples do not have diabetes
Setting threshold = 0, All samples do not have diabetes
Setting threshold = 1, All samples have diabetes
- 6. Multiple Choice
What is True (You may have multiple answer)
Training accuracy = 0.90, Testing accuracy = 0.89, your model is good enough to deploy for diabetes prediction
Area under curve of ROC is 0.9, your model is good enough to deploy for lung cancer prediction
Training accuracy = 0.90, Testing accuracy = 0.89, your model is not overfit
Area under curve of PR Curve is 0.9, your model is good enough to deploy for lung cancer prediction
- 7. Multiple Choice
What is limitation of over sampling?
It could make model underfit
It could make model overfit
- 8. Multiple Choice
What is limitation of under sampling
It could make model underfit
It could make model overfit
- 9. Multiple ChoiceThe margin of a linear classifier as the width that the boundary could be increased bybefore hitting a datapoint.nearer to data pointafter data pointmiddle of data poin
- 10. Multiple ChoiceHard Margindata points are classified partiallyall data points be classified correctlydata points are misclassifiednone of above
- 11. Multiple ChoiceWhich computer language is this?PythonBBC Micro:bit block codeScratch
- 12. Multiple ChoiceArtificial Intelligence is the process that allows computers to learn and make decisions like humansTrueFalse
- 13. Multiple ChoiceOvertime you log onto a website, you leave a mark. Your "stuff" can be seen, searched, copied, and forwarded to others. This permanent mark you leave is known as what?Digital MediaDigital FootprintCyberbullyingMedia
- 14. Multiple Choice
Which of these is an example of AI?
Able to burn a movie into DVD
Able to burn a movie into DVD
Able to understand human speech
Able to show you what is behind your car on the back up camera
- 15. Multiple Choice
An example of 'machine learning' is
a calculator that can do hard math problems
voicemail messages of your favorite celebrities
installing a new hard drive on a computer
a machine that improves performance based on watching a human do the same task
- 16. Multiple Choice
The purpose of AI is to...
Build computer programs that exhibit intelligent behavior
Build problems, learns and understand language.
Build emotions, language and understands mathematical problems.
Create a robot friend for every fifth grader
- 17. Multiple Choice
What would make a robot intelligent?
It responds to the environment.
It responds to the environment according to previous experiences.
It calculates mathematical problems faster than human minds.
It can jump 1.5 meters higher than humans.
- 18. Multiple Choice
Which of these is NOT always an example of AI?
GPS navigation
Amazon search engine
Siri or Alexa
- 19. Multiple Choice
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
- 20. Multiple Choice
Machine learning depends on
how smart the person on the computer is
having a good machine
accessing an ever-growing database of increasingly complex information
- 21. Multiple Choice
Which of these is an example of AI
back up camera on a car
a playlist you made on your iphone
a vacation ad based on your most recent Google search
a hover board
- 22. Multiple ChoiceWhich AI system finds and identifies patterns; for instance; in the words you use?Intelligent systemNeural networkFuzzy logicIntelligent agent
- 23. Multiple Choice
The cells that make up the nervous system are called
Glial
Neurons
Myelin
Neurocytes
- 24. Multiple Choice
A set of instructions to follow in order to solve a problem.
Algorithm
Machine learning
Neuron
Neural network
- 25. Multiple Choice
A basic unit of the brain, a cell designed to send information to other nerve cells, muscle, or gland cells.
Algorithm
Machine learning
Neuron
Neural network
- 26. Multiple Choice
type of machine learning which models itself after the human brain.
Algorithm
Machine learning
Neuron
Neural network
- 27. Multiple Choice
Several sets of data related to each other used to make decisions in machine learning algorithms. E.g. comments to make you happy and comments to make you sad
Dataset
supervised learning
unsupervised learning
Classifiers
- 28. Multiple Choice
Type of machine learning algorithm used to infer information from data without input from humans.
Dataset
supervised learning
unsupervised learning
Classifiers
- 29. Multiple Choice
All data is labeled and the algorithms learn to predict the output from the input data
Dataset
supervised learning
unsupervised learning
Classifiers
- 30. Multiple Choice
To identify and categorize opinions in text, in order to work out if the writer's attitude is positive, negative, or neutral.
Decision tree learning
Reinforcement learning
Predictive models
sentiment analysis
- 31. Multiple Choice
building a model that is capable of making predictions
Decision tree learning
Reinforcement learning
Predictive models
sentiment analysis
- 32. Multiple Choice
After training the ML model, we see how accurately it predicts the answer/responds. For example – does it cry when I say something mean to it?
Recognition
Training
Predictive models
Testing
- 33. Multiple Choice
an ML model needs this to generate data to learn from.
Recognition
Training
Predictive models
Testing
- 34. Multiple Choice
Automatic recognition of patterns in data (text, handwriting, images, sound and video)
Recognition
Training
Predictive models
Testing
- 35. Multiple Choice
In visualization shown above, fit of three different models (in blue line) on same training data. What can you conclude from these visualizations?
1) The training error in first model is higher when compared to second and third model.
2) The best model for this regression problem is the last (third) model, because it has minimum training error.
3) The second model is more robust than first and third because it will perform better on unseen data.
4) The third model is overfitting data as compared to first and second model.
5) All models will perform same because we have not seen the test data.
1 and 3
1 and 2
1,3 and 4
only 5
- 36. Multiple Choice
Which of the following can be used for clustering of data ?
Single layer perceptron
Multilayer perceptron
Self organizing map
Radial basis function
All of the above
- 37. Multiple Choice
Which Mathematical function is used to define Classification Algorithm in Machine Learning?
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